Abstract
Orthogonal Fourier-Mellin (OFM) moments have many desirable properties such as rotation invariance, robustness to noise, expression efficiency, fast computation and multi-level representation for describing the shapes of patterns, but there is a major drawback with OFM moments, they need to normalize an image to achieve scale invariance. This approach will take some errors since it involves the re-sampling and re-quantifying of digital images, and leads to inaccuracy of classifier. In this paper, we present an improved OFM moments, experiments show that the improved OFM moments not only have better rotation invariance, but also have scale invariance, the invariance of improved OFM moments have been greatly improved over the present methods.
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